Özet:

Today, e-learning in education & distance learning is the most popular way to gain knowledge and share information between learning communities. In India, formal learning phase is hard-hitting to lower middle class people due to economic background. To resolve this issue and improve the life standards of people, distance education based on e-learning and collaborative learning paves a way. Information retrieval domain supports in this to display the specific answer for the user query which makes the learning easier. Question answering system returns sentence segment rather than returning list of documents. We present a mobile based question answering system that serves as a personal assistant in learning and providing information about computers, software and hardware, book reviews using natural language.QA models accept the query in natural language, analyze and compare it with information stored in the knowledge base. It displays the optimized response snippets which improves the efficiency of e-learning retrieval responses. The proposed system was developed to help the users to learn the subject knowledge at times of examination, technical interview and share answer for other users. This paper proposes a technique to find the type of question that in turn leads to a correct answer. The knowledge base created from the benchmark dataset such as Amazon Book Reviews, 20newsgroup, Quora, and Yahoo! Answer. This paper also focuses on the Indian education scenario, eLearning tools for easy learning through content preparation and presentation. The system interface has been evaluated using standard metrics such as Precision, Fetch, F1 Score, Inverse Precision, and Inverse Recall for the appropriate relevant response.

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